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Include data for entire periods in response to recorder/statistics_during_period (#92848)
* Include data for entire periods in response to recorder/statistics_during_period * Break out function for calculating the end of the month
This commit is contained in:
Erik Montnemery
GitHub
parent
67d5ca4894
commit
c1f716487c
@ -981,6 +981,14 @@ def _reduce_statistics_per_week(
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)
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def _find_month_end_time(timestamp: datetime) -> datetime:
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"""Return the end of the month (midnight at the first day of the next month)."""
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# We add 4 days to the end to make sure we are in the next month
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return (timestamp.replace(day=28) + timedelta(days=4)).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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def reduce_month_ts_factory() -> (
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tuple[
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Callable[[float, float], bool],
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@ -1007,10 +1015,7 @@ def reduce_month_ts_factory() -> (
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start_local = _local_from_timestamp(time).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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# We add 4 days to the end to make sure we are in the next month
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end_local = (start_local.replace(day=28) + timedelta(days=4)).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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end_local = _find_month_end_time(start_local)
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return (
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start_local.astimezone(dt_util.UTC).timestamp(),
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end_local.astimezone(dt_util.UTC).timestamp(),
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@ -1629,6 +1634,36 @@ def _statistics_during_period_with_session(
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if statistic_ids is not None:
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metadata_ids = _extract_metadata_and_discard_impossible_columns(metadata, types)
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# Align start_time and end_time with the period
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if period == "day":
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start_time = dt_util.as_local(start_time).replace(
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hour=0, minute=0, second=0, microsecond=0
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)
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start_time = start_time.replace()
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if end_time is not None:
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end_local = dt_util.as_local(end_time)
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end_time = end_local.replace(
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hour=0, minute=0, second=0, microsecond=0
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) + timedelta(days=1)
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elif period == "week":
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start_local = dt_util.as_local(start_time)
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start_time = start_local.replace(
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hour=0, minute=0, second=0, microsecond=0
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) - timedelta(days=start_local.weekday())
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if end_time is not None:
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end_local = dt_util.as_local(end_time)
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end_time = (
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end_local.replace(hour=0, minute=0, second=0, microsecond=0)
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- timedelta(days=end_local.weekday())
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+ timedelta(days=7)
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)
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elif period == "month":
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start_time = dt_util.as_local(start_time).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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if end_time is not None:
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end_time = _find_month_end_time(dt_util.as_local(end_time))
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table: type[Statistics | StatisticsShortTerm] = (
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Statistics if period != "5minute" else StatisticsShortTerm
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)
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@ -961,7 +961,7 @@ def test_import_statistics_errors(
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@pytest.mark.parametrize("timezone", ["America/Regina", "Europe/Vienna", "UTC"])
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@pytest.mark.freeze_time("2022-10-01 00:00:00+00:00")
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def test_daily_statistics(
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def test_daily_statistics_sum(
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hass_recorder: Callable[..., HomeAssistant],
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caplog: pytest.LogCaptureFixture,
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timezone,
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@ -979,6 +979,8 @@ def test_daily_statistics(
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period2 = dt_util.as_utc(dt_util.parse_datetime("2022-10-03 23:00:00"))
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period3 = dt_util.as_utc(dt_util.parse_datetime("2022-10-04 00:00:00"))
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period4 = dt_util.as_utc(dt_util.parse_datetime("2022-10-04 23:00:00"))
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period5 = dt_util.as_utc(dt_util.parse_datetime("2022-10-05 00:00:00"))
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period6 = dt_util.as_utc(dt_util.parse_datetime("2022-10-05 23:00:00"))
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external_statistics = (
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{
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@ -1005,6 +1007,18 @@ def test_daily_statistics(
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"state": 3,
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"sum": 5,
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},
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{
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"start": period5,
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"last_reset": None,
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"state": 4,
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"sum": 6,
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},
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{
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"start": period6,
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"last_reset": None,
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"state": 5,
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"sum": 7,
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},
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)
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external_metadata = {
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"has_mean": False,
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@ -1024,6 +1038,8 @@ def test_daily_statistics(
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day1_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-04 00:00:00"))
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day2_start = dt_util.as_utc(dt_util.parse_datetime("2022-10-04 00:00:00"))
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day2_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-05 00:00:00"))
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day3_start = dt_util.as_utc(dt_util.parse_datetime("2022-10-05 00:00:00"))
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day3_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-06 00:00:00"))
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expected_stats = {
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"test:total_energy_import": [
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{
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@ -1040,6 +1056,13 @@ def test_daily_statistics(
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"state": 3.0,
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"sum": 5.0,
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},
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{
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"start": day3_start.timestamp(),
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"end": day3_end.timestamp(),
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"last_reset": None,
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"state": 5.0,
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"sum": 7.0,
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},
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]
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}
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assert stats == expected_stats
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@ -1064,6 +1087,11 @@ def test_daily_statistics(
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"end": day2_end.timestamp(),
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"change": 2.0,
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},
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{
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"start": day3_start.timestamp(),
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"end": day3_end.timestamp(),
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"change": 2.0,
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},
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]
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}
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@ -1076,6 +1104,16 @@ def test_daily_statistics(
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)
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assert stats == expected_stats
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# Get data with end during the third period
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stats = statistics_during_period(
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hass,
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start_time=zero,
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end_time=period6 - timedelta(hours=1),
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statistic_ids={"test:total_energy_import"},
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period="day",
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)
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assert stats == expected_stats
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# Try to get data for entities which do not exist
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stats = statistics_during_period(
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hass,
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@ -1106,7 +1144,7 @@ def test_daily_statistics(
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@pytest.mark.parametrize("timezone", ["America/Regina", "Europe/Vienna", "UTC"])
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@pytest.mark.freeze_time("2022-10-01 00:00:00+00:00")
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def test_weekly_statistics(
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def test_weekly_statistics_mean(
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hass_recorder: Callable[..., HomeAssistant],
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caplog: pytest.LogCaptureFixture,
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timezone,
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@ -1121,7 +1159,7 @@ def test_weekly_statistics(
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zero = dt_util.utcnow()
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period1 = dt_util.as_utc(dt_util.parse_datetime("2022-10-03 00:00:00"))
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period2 = dt_util.as_utc(dt_util.parse_datetime("2022-10-09 23:00:00"))
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period2 = dt_util.as_utc(dt_util.parse_datetime("2022-10-05 23:00:00"))
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period3 = dt_util.as_utc(dt_util.parse_datetime("2022-10-10 00:00:00"))
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period4 = dt_util.as_utc(dt_util.parse_datetime("2022-10-16 23:00:00"))
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@ -1129,31 +1167,35 @@ def test_weekly_statistics(
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{
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"start": period1,
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"last_reset": None,
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"state": 0,
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"sum": 2,
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"max": 0,
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"mean": 10,
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"min": -100,
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},
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{
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"start": period2,
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"last_reset": None,
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"state": 1,
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"sum": 3,
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"max": 10,
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"mean": 20,
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"min": -90,
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},
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{
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"start": period3,
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"last_reset": None,
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"state": 2,
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"sum": 4,
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"max": 20,
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"mean": 30,
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"min": -80,
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},
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{
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"start": period4,
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"last_reset": None,
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"state": 3,
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"sum": 5,
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"max": 30,
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"mean": 40,
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"min": -70,
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},
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)
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external_metadata = {
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"has_mean": False,
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"has_sum": True,
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"has_mean": True,
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"has_sum": False,
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"name": "Total imported energy",
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"source": "test",
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"statistic_id": "test:total_energy_import",
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@ -1162,6 +1204,7 @@ def test_weekly_statistics(
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async_add_external_statistics(hass, external_metadata, external_statistics)
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wait_recording_done(hass)
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# Get all data
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stats = statistics_during_period(
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hass, zero, period="week", statistic_ids={"test:total_energy_import"}
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)
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@ -1175,42 +1218,30 @@ def test_weekly_statistics(
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"start": week1_start.timestamp(),
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"end": week1_end.timestamp(),
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"last_reset": None,
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"state": 1.0,
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"sum": 3.0,
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"max": 10,
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"mean": 15,
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"min": -100,
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},
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{
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"start": week2_start.timestamp(),
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"end": week2_end.timestamp(),
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"last_reset": None,
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"state": 3.0,
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"sum": 5.0,
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"max": 30,
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"mean": 35,
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"min": -80,
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},
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]
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}
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assert stats == expected_stats
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# Get change
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# Get data starting with start of the first period
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stats = statistics_during_period(
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hass,
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start_time=period1,
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statistic_ids={"test:total_energy_import"},
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period="week",
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types={"change"},
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)
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assert stats == {
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"test:total_energy_import": [
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{
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"start": week1_start.timestamp(),
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"end": week1_end.timestamp(),
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"change": 3.0,
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},
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{
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"start": week2_start.timestamp(),
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"end": week2_end.timestamp(),
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"change": 2.0,
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},
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]
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}
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assert stats == expected_stats
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# Get data with start during the first period
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stats = statistics_during_period(
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@ -1250,13 +1281,13 @@ def test_weekly_statistics(
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@pytest.mark.parametrize("timezone", ["America/Regina", "Europe/Vienna", "UTC"])
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@pytest.mark.freeze_time("2021-08-01 00:00:00+00:00")
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def test_monthly_statistics(
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@pytest.mark.freeze_time("2022-10-01 00:00:00+00:00")
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def test_weekly_statistics_sum(
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hass_recorder: Callable[..., HomeAssistant],
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caplog: pytest.LogCaptureFixture,
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timezone,
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) -> None:
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"""Test monthly statistics."""
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"""Test weekly statistics."""
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dt_util.set_default_time_zone(dt_util.get_time_zone(timezone))
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hass = hass_recorder()
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@ -1265,10 +1296,12 @@ def test_monthly_statistics(
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assert "Statistics already compiled" not in caplog.text
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zero = dt_util.utcnow()
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period1 = dt_util.as_utc(dt_util.parse_datetime("2021-09-01 00:00:00"))
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period2 = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 23:00:00"))
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period3 = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
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period4 = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 23:00:00"))
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period1 = dt_util.as_utc(dt_util.parse_datetime("2022-10-03 00:00:00"))
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period2 = dt_util.as_utc(dt_util.parse_datetime("2022-10-09 23:00:00"))
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period3 = dt_util.as_utc(dt_util.parse_datetime("2022-10-10 00:00:00"))
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period4 = dt_util.as_utc(dt_util.parse_datetime("2022-10-16 23:00:00"))
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period5 = dt_util.as_utc(dt_util.parse_datetime("2022-10-17 00:00:00"))
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period6 = dt_util.as_utc(dt_util.parse_datetime("2022-10-23 23:00:00"))
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external_statistics = (
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{
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@ -1295,6 +1328,201 @@ def test_monthly_statistics(
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"state": 3,
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"sum": 5,
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},
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{
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"start": period5,
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"last_reset": None,
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"state": 4,
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"sum": 6,
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},
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{
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"start": period6,
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"last_reset": None,
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"state": 5,
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"sum": 7,
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},
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)
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external_metadata = {
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"has_mean": False,
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"has_sum": True,
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"name": "Total imported energy",
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"source": "test",
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"statistic_id": "test:total_energy_import",
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"unit_of_measurement": "kWh",
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}
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async_add_external_statistics(hass, external_metadata, external_statistics)
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wait_recording_done(hass)
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stats = statistics_during_period(
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hass, zero, period="week", statistic_ids={"test:total_energy_import"}
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)
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week1_start = dt_util.as_utc(dt_util.parse_datetime("2022-10-03 00:00:00"))
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week1_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-10 00:00:00"))
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week2_start = dt_util.as_utc(dt_util.parse_datetime("2022-10-10 00:00:00"))
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week2_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-17 00:00:00"))
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week3_start = dt_util.as_utc(dt_util.parse_datetime("2022-10-17 00:00:00"))
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week3_end = dt_util.as_utc(dt_util.parse_datetime("2022-10-24 00:00:00"))
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expected_stats = {
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"test:total_energy_import": [
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{
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"start": week1_start.timestamp(),
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"end": week1_end.timestamp(),
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"last_reset": None,
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"state": 1.0,
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"sum": 3.0,
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},
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{
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"start": week2_start.timestamp(),
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"end": week2_end.timestamp(),
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"last_reset": None,
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"state": 3.0,
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"sum": 5.0,
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},
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{
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"start": week3_start.timestamp(),
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"end": week3_end.timestamp(),
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"last_reset": None,
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"state": 5.0,
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"sum": 7.0,
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},
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]
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}
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assert stats == expected_stats
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# Get change
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stats = statistics_during_period(
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hass,
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start_time=period1,
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statistic_ids={"test:total_energy_import"},
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period="week",
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types={"change"},
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)
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assert stats == {
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"test:total_energy_import": [
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{
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"start": week1_start.timestamp(),
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"end": week1_end.timestamp(),
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"change": 3.0,
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},
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{
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"start": week2_start.timestamp(),
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"end": week2_end.timestamp(),
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"change": 2.0,
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},
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{
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"start": week3_start.timestamp(),
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"end": week3_end.timestamp(),
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"change": 2.0,
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},
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]
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}
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# Get data with start during the first period
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stats = statistics_during_period(
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hass,
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start_time=period1 + timedelta(days=1),
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statistic_ids={"test:total_energy_import"},
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period="week",
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)
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assert stats == expected_stats
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# Get data with end during the third period
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stats = statistics_during_period(
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hass,
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start_time=zero,
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end_time=period6 - timedelta(days=1),
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statistic_ids={"test:total_energy_import"},
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period="week",
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)
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assert stats == expected_stats
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# Try to get data for entities which do not exist
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stats = statistics_during_period(
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hass,
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start_time=zero,
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statistic_ids={"not", "the", "same", "test:total_energy_import"},
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period="week",
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)
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assert stats == expected_stats
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# Use 5minute to ensure table switch works
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stats = statistics_during_period(
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hass,
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start_time=zero,
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statistic_ids=["test:total_energy_import", "with_other"],
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period="5minute",
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)
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assert stats == {}
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# Ensure future date has not data
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future = dt_util.as_utc(dt_util.parse_datetime("2221-11-01 00:00:00"))
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stats = statistics_during_period(
|
||||
hass, start_time=future, end_time=future, period="week"
|
||||
)
|
||||
assert stats == {}
|
||||
|
||||
dt_util.set_default_time_zone(dt_util.get_time_zone("UTC"))
|
||||
|
||||
|
||||
@pytest.mark.parametrize("timezone", ["America/Regina", "Europe/Vienna", "UTC"])
|
||||
@pytest.mark.freeze_time("2021-08-01 00:00:00+00:00")
|
||||
def test_monthly_statistics_sum(
|
||||
hass_recorder: Callable[..., HomeAssistant],
|
||||
caplog: pytest.LogCaptureFixture,
|
||||
timezone,
|
||||
) -> None:
|
||||
"""Test monthly statistics."""
|
||||
dt_util.set_default_time_zone(dt_util.get_time_zone(timezone))
|
||||
|
||||
hass = hass_recorder()
|
||||
wait_recording_done(hass)
|
||||
assert "Compiling statistics for" not in caplog.text
|
||||
assert "Statistics already compiled" not in caplog.text
|
||||
|
||||
zero = dt_util.utcnow()
|
||||
period1 = dt_util.as_utc(dt_util.parse_datetime("2021-09-01 00:00:00"))
|
||||
period2 = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 23:00:00"))
|
||||
period3 = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
|
||||
period4 = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 23:00:00"))
|
||||
period5 = dt_util.as_utc(dt_util.parse_datetime("2021-11-01 00:00:00"))
|
||||
period6 = dt_util.as_utc(dt_util.parse_datetime("2021-11-30 23:00:00"))
|
||||
|
||||
external_statistics = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"state": 0,
|
||||
"sum": 2,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"state": 1,
|
||||
"sum": 3,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"state": 2,
|
||||
"sum": 4,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"state": 3,
|
||||
"sum": 5,
|
||||
},
|
||||
{
|
||||
"start": period5,
|
||||
"last_reset": None,
|
||||
"state": 4,
|
||||
"sum": 6,
|
||||
},
|
||||
{
|
||||
"start": period6,
|
||||
"last_reset": None,
|
||||
"state": 5,
|
||||
"sum": 7,
|
||||
},
|
||||
)
|
||||
external_metadata = {
|
||||
"has_mean": False,
|
||||
@ -1314,6 +1542,8 @@ def test_monthly_statistics(
|
||||
sep_end = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
|
||||
oct_start = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
|
||||
oct_end = dt_util.as_utc(dt_util.parse_datetime("2021-11-01 00:00:00"))
|
||||
nov_start = dt_util.as_utc(dt_util.parse_datetime("2021-11-01 00:00:00"))
|
||||
nov_end = dt_util.as_utc(dt_util.parse_datetime("2021-12-01 00:00:00"))
|
||||
expected_stats = {
|
||||
"test:total_energy_import": [
|
||||
{
|
||||
@ -1330,6 +1560,13 @@ def test_monthly_statistics(
|
||||
"state": pytest.approx(3.0),
|
||||
"sum": pytest.approx(5.0),
|
||||
},
|
||||
{
|
||||
"start": nov_start.timestamp(),
|
||||
"end": nov_end.timestamp(),
|
||||
"last_reset": None,
|
||||
"state": 5.0,
|
||||
"sum": 7.0,
|
||||
},
|
||||
]
|
||||
}
|
||||
assert stats == expected_stats
|
||||
@ -1354,6 +1591,11 @@ def test_monthly_statistics(
|
||||
"end": oct_end.timestamp(),
|
||||
"change": 2.0,
|
||||
},
|
||||
{
|
||||
"start": nov_start.timestamp(),
|
||||
"end": nov_end.timestamp(),
|
||||
"change": 2.0,
|
||||
},
|
||||
]
|
||||
}
|
||||
# Get data with start during the first period
|
||||
@ -1365,6 +1607,16 @@ def test_monthly_statistics(
|
||||
)
|
||||
assert stats == expected_stats
|
||||
|
||||
# Get data with end during the third period
|
||||
stats = statistics_during_period(
|
||||
hass,
|
||||
start_time=zero,
|
||||
end_time=period6 - timedelta(days=1),
|
||||
statistic_ids={"test:total_energy_import"},
|
||||
period="month",
|
||||
)
|
||||
assert stats == expected_stats
|
||||
|
||||
# Try to get data for entities which do not exist
|
||||
stats = statistics_during_period(
|
||||
hass,
|
||||
@ -1394,6 +1646,11 @@ def test_monthly_statistics(
|
||||
"end": oct_end.timestamp(),
|
||||
"sum": pytest.approx(5.0),
|
||||
},
|
||||
{
|
||||
"start": nov_start.timestamp(),
|
||||
"end": nov_end.timestamp(),
|
||||
"sum": pytest.approx(7.0),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
@ -1418,6 +1675,11 @@ def test_monthly_statistics(
|
||||
"end": oct_end.timestamp(),
|
||||
"sum": pytest.approx(5000.0),
|
||||
},
|
||||
{
|
||||
"start": nov_start.timestamp(),
|
||||
"end": nov_end.timestamp(),
|
||||
"sum": pytest.approx(7000.0),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user